bfindep

Computes a Bayes factor against independence for a two-way contingency table assuming
a "close to independence" alternative model

models

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

bfindep function

<dl> <dt>y</dt>
<dd>matrix of counts</dd> <dt>K</dt>
<dd>Dirichlet precision hyperparameter</dd> <dt>m</dt>
<dd>number of simulations</dd></dl>

Arguments

Author

Bayes factor against independence assuming alternatives close to independence — bfindep

<dl>

 <dt>y</dt>
<dd>matrix of counts</dd>

 <dt>K</dt>
<dd>Dirichlet precision hyperparameter</dd>

 <dt>m</dt>
<dd>number of simulations</dd>

</dl>

bfindep: Bayes factor against independence assuming alternatives close to independence

Description

Usage

Value

Arguments

Author

Examples